Almost all known production-car driver assistance systems based on data of surroundings-covering sensor systems use an object-abstract model of the surroundings. Typically, an object list containing objects in the surroundings is provided. Object-free areas defining a potential maneuver space are not covered by such an approach. There are known approaches in research that propose the use of sensors that provide a piece of occupancy information about a defined region in the surroundings of the vehicle and plot said piece of information on a map of occupancy. The map of occupancy is preferably designed as a probability grid containing at least one probability value per grid cell, e.g., whether there is an object in this space segment in the surroundings of the vehicle, i.e., whether the cell is occupied. A probability grid requires a spatial discretization of the surroundings of the vehicle.
Aside from a discretization with a constant step size, discretization methods supporting various steps of resolution may be used, wherein known structures are, above all, quadtrees in the two-dimensional space and octtrees in the three-dimensional space based on a recursive subdivision of an area into quarters, which is shown in FIG. 1a by way of example. A tree-like data structure may be used to store the data (probability values), which is shown in FIG. 1b by way of example.